How to Improve the Usage Rate of An E-commerce Application; User Acceptance Testing of E-Commerce Services

The global prevalence of the Internet has encouraged many businesses to shift their operations to e-commerce platforms. Today, most of the businesses are performing on their e-commerce platforms as well as keeping on their physical presence, or they are following plans to run online in the near future. It is evident that a great number of e-commerce projects may fail because of various reasons ranging from misunderstanding about objectives, underestimating financial costs or failure in running a secure electronic commerce service. One remarkable reason to fail is end-users’ refusal. Users may refuse to use an e-commerce service because one e-commerce service does not provide their preferred specifications or does not seem to be adequately secure and private to fully rely on. Rejection of users leads to their disappointment about an e-commerce service and finally failure of one e-commerce service. Thus, it is becoming inevitable for decision-makers to assess user acceptance of an e-commerce service through comprehensive models.

As businesses and customers are encouraged to the utilization of e-commerce platforms, the prevalence of e-commerce services that facilitate the operation of internet-based interactions increases as well. Information technology tools and techniques are widely employed to modernize businesses and to switch the economy from goods to services. E-commerce services that originally refer to the services provided through electronic channels are considered as fundamentals of digital aged businesses (Hamed Taherdoost, 2020b). A significant number of businesses rely on e-commerce services provided on the screen. E-commerce minimizes or even eliminates the necessity for physical presence and contact between clients and staff (Hamed Taherdoost, 2016). As a consequence, the operational cost will decrease to an acceptable extent. Thus, it is crucial for various business sectors to provide e-commerce establishments in order to differentiate and segment their business in the market. The application of e-commerce in governments, education systems, transportation systems, financial services, healthcare, and retail services has become mandatory mostly because of the over-reliance of individuals on these systems on a daily basis. The usage of e-commerce is beneficial for both end-users and service providers. It helps businesses to deliver their products and services effectively through online platforms, and promotes services in different aspects such as providing advanced user interactions, efficient information management, acceptable accountability and transparency, customer satisfaction, wide accessibility and reduced cost. 

User acceptance in e-commerce services is mainly associated with the decision made by users to adopt, refuse or continue to use e-commerce based on their perception about the function of the service. Therefore, development of an e-commerce is strongly tied with recognition of root causes that encourage users to accept using e-commerce. Understanding the perception of users as a major role player in determining the success or failure of implementing a service is crucial in today’s dynamic business atmosphere. It is stated that the gap between the actual characteristics of an e-commerce service and users’ perception leaves an influential impact on individuals’ behavior and decision to adopt an e-commerce service.

Users’ acceptance can be assessed through evaluating certain factors of various models. Several models have been introduced to address the attitude of users in accepting or rejecting new technologies and innovations regarding determining factors (Hamed Taherdoost, 2018b). However, it has been stated that traditional acceptance models do not appropriately suffice to explain and predict the users’ acceptance of new services delivered via digital channels since they are limited to a single application, geographical zone or other specifications. One crucial barrier that prevents users from adopting e-commerce and needs to be considered serious while developing an e-commerce service is the reluctance to share personal information via unsecure electronic channels (H. Taherdoost, 2017). A comprehensive model has been developed and defined effective factors influencing user acceptance of e-services which also covers main serious concerns of e-commerce users such as security and privacy that are presented to assess users’ acceptance of any e-commerce service (Hamed Taherdoost, 2018a). The purpose of this model which is entitled “E-Service Technology Acceptance Model” (Hamed Taherdoost, 2018a) is to assess major factors affecting the acceptance of e-services including satisfaction, security and quality. The conceptual model which includes 15 different variables (ETAM) is presented in Figure 1 adapted from Hamed Taherdoost (2018a). E-Service Technology Acceptance Model (ETAM) can be used to assess the user acceptance of any kind of e-commerce service.

This is a comprehensive model that includes the most important indicators of users’ intention to use e-commerce services and is also in accordance with new trends in e-commerce services. The utilization of this model that is regarded as an effective tool in the improvement of e-commerce implementation process, helps managers to assess, monitor and realize the process of e-commerce acceptance by considering the main factors influencing the acceptance of e-services, namely satisfaction, security and quality.

As end-users’ decision to accept or reject a technology is vital for its success, it is necessary for decision-makers to assess the level of users’ acceptance about one e-commerce before developing or improving it. The intention to use or reject an e-commerce service by users is significantly correlated with satisfaction, privacy, security and quality. Deploying a comprehensive model to assess users’ acceptance is highly recommended for service providers while developing e-commerce platforms and policies. The application of the presented model in understanding users’ attitude towards e-commerce services guides decision-makers in providing appropriate strategies before starting to run or improve an e-commerce project and encourages people to use their e-commerce services.

For more detail please refer to below two articles:

1) Taherdoost, H. (2018a). Development of an adoption model to assess user acceptance of e-service technology: E-Service Technology Acceptance Model. Behaviour & Information Technology, 37(2), 173-197.

2) Taherdoost, H. (2020). User Acceptance Assessment of E-Commerce Services; How to Improve the Usage Rate of An E-commerce Application, International Journal of Advanced Computer Science and Information Technology, Vol. 9, No. 1, 2020, Page: 1-5.

References:

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Kuhl J.and Beckmann J.(eds.). Action Control: From Cognition to Behavior. New York: Springer-Verlag, 3, 11-39.

Interactive, H. (2006). Making new waves in market research. Retrieved from

Taherdoost, H. (2016). Electronic Service Technology; Concepts, Applications and Security (1st ed.). Saarbrücken, Germany: OmniScriptum.

Taherdoost, H. (2017). Understanding of E-service Security Dimensions and its effect on Quality and Intention to Use. Information and Computer Security, Accepted and in Press. .

Taherdoost, H. (2018a). Development of an adoption model to assess user acceptance of e-service technology: E-Service Technology Acceptance Model. Behaviour & Information Technology, 37(2), 173-197.

Taherdoost, H. (2018b). A Review of Technology Acceptance and Adoption Models and Theories. Procedia Manufacturing Journal, 22, 960–967.

Taherdoost, H. (2020a). Electronic Service Quality Measurement (eSQM); Development of a Survey Instrument to Measure the Quality of E-Service. International Journal of Intelligent Engineering Informatics, 7(6), 491-528.

Taherdoost, H. (2020b). Evaluation of Customer Satisfaction in Digital Environment; Development of Survey Instrument. In K. Sandhu (Ed.), Digital Transformation and Innovative Services for Business and Learning (pp. 195-222): IGI Global.

Taherdoost, H., & Hassan, A. (2020). Development of An E-Service Quality Model (eSQM) to Assess the Quality of E-Service. In R. C. Ho (Ed.), Strategies and Tools for Managing Connected Customers (pp. 177-207): IGI Global.

Taherdoost, H., & Madanchian, M. (2020). Developing and Validating a Theoretical Model to Evaluate Customer Satisfaction of E-Services. In K. Sandhu (Ed.), Digital Innovations for Customer Engagement, Management and Organizational Improvement (pp. 46-65. ): IGI Global.

Tan, C.-W., Benbasat, I., & Cenfetelli, R. T. (2011). Understanding e-service failures: formation, impact and recovery. Paper presented at the Tenth Annual Workshop on HCI Research in MIS, Shanghai, China.